Image Pixel Average Color

No. This tool processes images entirely within your browser using the HTML5 Canvas API. Your file is loaded as a temporary object URL and pixel data never leaves your device — no logging of your image and no external API calls.

Different algorithms solve different problems:

• Mean — Fastest, best for solid-color regions
• Median — Ignores outliers like bright highlights or dark shadows
• Dominant — Finds the most common color cluster, ideal for multi-colored images
• Brightness-weighted — Prioritizes perceptually brighter areas, matches human attention Use median for photos with glare, dominant for logos with multiple colors, brightness-weighted when the subject is lighter than its background.

OKLCH is a perceptually uniform color space that represents colors as lightness, chroma, and hue. Unlike HSL where lightness: 50% looks different for different hues, OKLCH lightness is visually consistent across the color wheel. It's now supported in all modern browsers and is ideal for design systems and accessibility work.

Enable Exclude Pixels filters in the control panel:

• Check "Transparent" for PNGs with alpha channels
• Check "Near-white" for white/light backgrounds (adjust threshold 200-255)
• Check "Near-black" for black/dark backgrounds (adjust threshold 0-50) These filters run before averaging, so background pixels don't skew your result.

Sampling rate determines how many pixels are analyzed:

• 1 = Every pixel (highest accuracy, slower)
• 5 = Every 5th pixel (good balance)
• 10+ = Every 10th+ pixel (fastest, slight quality loss) For most images, rate 5-10 is visually identical to full sampling while processing 10-100× faster.

Several factors affect color extraction:

1. Color space conversion — Browsers display sRGB; OKLCH/RGB values may appear different when converted back
2. Outlier sensitivity — Mean algorithm is affected by bright/dark spots; try Median or Dominant
3. Gamma correction — Canvas reads display-referred pixels, not scene-referred camera data
4. Browser color management — Different systems apply different ICC profiles For critical brand colors, verify with the live preview swatch and compare against your source file in a color-managed application.

WCAG (Web Content Accessibility Guidelines) defines minimum contrast ratios for text readability:

• 4.5:1 — Minimum for normal text (AA)
• 7:1 — Enhanced for normal text (AAA)
• 3:1 — Minimum for large text (18pt+) or UI components (AA) Low contrast causes eye strain and excludes users with low vision. This tool calculates contrast against pure white and black so you can choose accessible background colors.

Currently the tool processes one image at a time for interactive control. For batch processing, you can:

1. Process each image individually and record values
2. Use the CSS variables output to build a design token file
3. Re-upload the same image with different algorithms to compare results Batch automation is not supported to maintain the client-side privacy guarantee.

Large images consume significant browser memory:

• A 100MP image (e.g., 12000×8000) requires ~480MB RAM as uncompressed RGBA data
• Canvas operations are synchronous and block the main thread
• Mobile devices may crash with excessive memory use The 50MB limit and 2048px downscaling ensure reliable performance across devices. For larger files, resize in an image editor first — color accuracy is preserved at 2048px for most purposes.

The dominant color uses k-means clustering with k=1 and iterative refinement:

1. Seed with median color for stability
2. Weight pixels by inverse distance to current center
3. Recalculate center 10 iterations or until convergence This finds the color that minimizes average distance to all valid pixels — the "most representative" color rather than the mathematical average. It's robust to bimodal distributions (e.g., blue sky + green grass) where mean would produce muddy gray.

Not directly. Extract a frame using your video player or browser dev tools, save as PNG, then upload. For automated video analysis, the underlying algorithms could be adapted to sample <video> elements via drawImage() to canvas, but this tool focuses on static image workflow.

Any browser supporting:

• HTML5 Canvas getImageData()
• Image.decode() or Image.onload
• ES2020 (BigInt, optional chaining)
• CSS oklch() (for preview display, not core functionality) This includes Chrome 111+, Firefox 113+, Safari 16.4+, Edge 111+. Internet Explorer is not supported.

This occurs when your exclusion filters remove every valid pixel:

• Transparent PNG — Check "Exclude transparent" with fully transparent image
• Near-white/black thresholds — Thresholds of 250/5 are strict; try relaxing to 240/15
• Monochrome images — Pure black/white images may have no valid pixels after filtering Disable all exclusions or adjust thresholds to resolve.

Each design tool accepts different formats:

Both are cylindrical color spaces (lightness, chroma, hue), but:

• LCH — Based on CIELAB (1976), widely used in print and legacy systems
• OKLCH — Based on Oklab (2020), better hue linearity, recommended for web OKLCH is preferred for digital design; LCH is provided for compatibility with older color workflows. Modern CSS lch() and oklch() functions are both supported in current browsers.